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Accurate 3D localisation of mobile target using single station with AoA–TDoA measurements

机译:使用具有AOA-TDOA测量的单站精确的移动目标3D定位

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An attractive and challenging problem in source localisation is to locate a target in three-dimensional (3D) space using a single station. To satisfy the observability requirements and achieve higher accuracy, the authors draw on the idea of the inverse synthetic aperture radar for single-station localisation, which leverages the mobility of target and a time serial measurements of angle of arrival (AoA) and time difference of arrival (TDoA). A closed-form pseudo-linear estimator (PLE) is developed to estimate both 3D position and velocity of mobile target through the linearisation of AoA-TDoA measurement equations. Furthermore, to suppress the large bias of PLE caused by the correlation of measurement noise, the authors propose a superior bias-reduced estimator (BRE), which imposes a quadratic constraint to minimise the noise correlation term. They prove that BRE is asymptotically efficient, attaining the Cramer-Rao lower bound (CRLB) over the moderate noise region. Extensive simulations show that both bias and mean square error of BRE are well predicted by theoretical analysis. Most importantly, in comparison with both PLE and two traditional bias reduction methods, namely weighted total least squares and weighted instrumental variables, BRE can approach the CRLB over a wider noise region and maintain a lower bias.
机译:源定位中有吸引力和具有挑战性的问题是使用单个站定位三维(3D)空间中的目标。为了满足可观察性要求并实现更高的准确性,作者利用单站定位的逆合成孔径雷达的思想,利用目标的移动性和时间串行测量的到达角度(AOA)和时间差到达(TDOA)。开发出闭合伪线性估计器(PLE)以通过AOA-TDOA测量方程的线性化来估计移动目标的3D位置和速度。此外,为了抑制由测量噪声的相关性引起的大偏压,作者提出了一种优异的偏差估计器(BRE),其施加了二次约束以最小化噪声相关项。他们证明,BRE是渐近的有效性,达到克拉梅勒 - RAO下限(CRLB)在中等噪声区域上。广泛的模拟表明,通过理论分析,BRE的偏差和均方误差均得到很好的预测。最重要的是,与PLE和两个传统的偏差减少方法相比,即加权总量最小二乘和加权仪器变量,BRE可以在更宽的噪声区域上接近CRLB并保持较低的偏置。

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